| 温室智能控制系统适用性评价指标体系选择模型 |
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| 引用本文： | 李 琳,张领先,李道亮,秦向阳,刘 雪.温室智能控制系统适用性评价指标体系选择模型[J].农业工程学报,2012,28(3):148-153. |
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| 作者姓名： | 李 琳 张领先 李道亮 秦向阳 刘 雪 |
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| 作者单位： | 1. 中国农业大学大学信息与电气工程学院,北京,100083
2. 国家农业信息化工程技术研究中心,北京,100083 |
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| 基金项目： | 公益性行业（农业）科研专项“现代农业公共服务装备与设施工程（200903009） |
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| 摘 要： | 针对温室智能控制系统适用性评价体系中指标设置的随意性和冗余性问题,本着满足指标简洁性并兼顾完备性的目标,该文在分析影响温室智能控制系统因素的基础上,探索了选取和优化温室智能控制系统适用性评价指标体系的方法,并构建了基于选择模型的温室智能控制系统适用性评价指标体系。山东省寿光蔬菜基地的实证分析表明,该区域的温室智能控制系统适用性评价指标能够从32个优化到22个,指标的完备性达到88.96%,实现了优化指标数和减少指标干扰的要求,为温室智能控制系统的适用性评价提供参考。
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| 关 键 词： | 温室 智能控制系统 模型 适用性评价 指标优化 |
| 收稿时间： | 2011/6/14 0:00:00 |
| 修稿时间： | 2011/7/29 0:00:00 |
Indicators selecting model for applicability evaluation of greenhouse intelligent control system |
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| Li Lin,Zhang Lingxian,Li Daoliang,Qin Xiangyang and Liu Xue.Indicators selecting model for applicability evaluation of greenhouse intelligent control system[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(3):148-153. |
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| Authors: | Li Lin Zhang Lingxian Li Daoliang Qin Xiangyang and Liu Xue |
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| Institution: | 1 (1.Department of Information and Electrical Engineering,China Agricultural University,Beijing 100083,China;2.National Engineering Research Center for Information Technology in Agriculture,Beijing 100083,China) |
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| Abstract: | In order to solve the problem of randomness and repetitiveness, the paper explored the methodology for selection and optimization of indicators for the applicability evaluation of greenhouse intelligent control systems indicators based on analyzing the factors influencing the greenhouse intelligent control system. An indicator selection model for applicability assessment of greenhouse intelligent control system was constructed and Shouguang Vegetable Greenhouse was taken as an example for empirical study, which showed that the indicators could be optimized from 32 to 22 by using the selection model and the completeness of indexes system reached as high as 88.96%. Consequently, the objective to reduce the randomness, completeness and simplicity of indicators selection can achieve. The results can provide a foundation for further applicability evaluation of greenhouse intelligent control systems. |
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| Keywords: | greenhouse intelligent control system models applicability evaluation indicators optimization |
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